Mobile communication devices, such as a cell phone or radio, are used primarily for voice communication. In certain environments, speech may be contaminated with unwanted noise. The noise may be background noise, such as car noise, street noise, or babble noise, that is audibly present in the environment and that degrades the intelligibility of the speech. Mobile communication devices generally include a noise suppressor for suppressing unwanted noise in the speech. The noise suppressor may be a stand-alone module, or a module integrated within a vocoder. As shown in FIG. 1, a mobile communication device generally includes a microphone 20 for capturing speech, an analog to digital converter 30 for generating a digital signal from the speech, an equalizer 40 for adjusting an equalization of the digital signal, a vocoder 50 for compressing the equalized signal, and a modem 60 for transmitting the compressed signal. The input to the microphone 20 may consist of speech and unwanted noise. The vocoder 50 can include an internal noise suppressor 100 that suppresses unwanted noise, such as background noise, in the input signal.
A vocoder 50, such as the Enhanced Variable Rate Coder (EVRC), is a voice compression system used with the International Standard (IS-95) Rate 1 CDMA interface. The EVRC employs an adaptive noise suppressor (NS) 100 for suppressing unwanted noise in an input signal. The adaptive NS 100 is based on a spectral subtraction technique that effectively subtracts a noise estimate from the input signal. The adaptive NS 100 requires a good estimate of the noise to achieve acceptable noise suppression. The noise can be estimated during times of silence, or non-speech activity. The adaptive NS 100 relies on an assumption that the noise (generally background noise) is stationary or slowly varying non-stationary. This allows the adaptive NS 100 to generate a reliable estimate of the noise during non-speech activity.
However, when a rapidly varying or abrupt noise is introduced to the input signal, the adaptive NS 100 misinterprets the noise as speech. Consequently, the adaptive NS 100 does not update the noise estimate nor immediately suppress the noise. As a result, the adaptive NS 100 can only suppresses noise in accordance with a previous noise estimate. This delay in immediately recognizing the noise leaves much noise that is unsuppressed for a significant period afterwards. Over time the adaptive NS 100 will recognize the noise, update an estimate of the noise, and begin the noise suppression process. However, during this time, the unwanted noise is audible and present in the compressed speech signal. A need therefore exists for improving the detection and suppression of abrupt noise in a signal.